Expression Heatmap
Group 1 vs. Group 2
z_scores <- inner_join(counts, DE_genes) %>%
subset(select = -c(gene)) %>%
filter(transition == 'fc_1-15_16-26') %>%
group_by(ensembl_id) %>%
mutate(counts = scale(counts)) %>%
spread(key = age_group, value = counts) %>%
column_to_rownames(var = 'ensembl_id') %>%
subset(select = -transition)
## Joining, by = "gene"
colnames(z_scores) <- c("Group 1", "Group 2", "Group 3", "Group 4", "Group 5")
pheatmap(t(z_scores), cluster_rows = FALSE, show_colnames = FALSE, fontsize = 22)

Group 2 vs. Group 3
z_scores <- inner_join(counts, DE_genes) %>%
subset(select = -c(gene)) %>%
filter(transition == 'fc_16-26_27-60') %>%
group_by(ensembl_id) %>%
mutate(counts = scale(counts)) %>%
spread(key = age_group, value = counts) %>%
column_to_rownames(var = 'ensembl_id') %>%
subset(select = -transition)
## Joining, by = "gene"
colnames(z_scores) <- c("Group 1", "Group 2", "Group 3", "Group 4", "Group 5")
out <- pheatmap(t(z_scores), cluster_rows = FALSE, show_colnames = FALSE, fontsize = 22)

gene_order <- rownames(z_scores[out$tree_col[["order"]], ])
gene_order <- c(gene_order[27:162], gene_order[1:26])
pheatmap(t(z_scores[gene_order, ]), cluster_rows = FALSE, cluster_cols = FALSE, show_colnames = FALSE, fontsize = 22)

Group 3 vs. Group 4
z_scores <- inner_join(counts, DE_genes) %>%
subset(select = -c(gene)) %>%
filter(transition == 'fc_27-60_61-85') %>%
group_by(ensembl_id) %>%
mutate(counts = scale(counts)) %>%
spread(key = age_group, value = counts) %>%
column_to_rownames(var = 'ensembl_id') %>%
subset(select = -transition)
## Joining, by = "gene"
colnames(z_scores) <- c("Group 1", "Group 2", "Group 3", "Group 4", "Group 5")
pheatmap(t(z_scores), cluster_rows = FALSE, show_colnames = FALSE, fontsize = 22)

Group 4 vs. Group 5
z_scores <- inner_join(counts, DE_genes) %>%
subset(select = -c(gene)) %>%
filter(transition == 'fc_61-85_86-96') %>%
group_by(ensembl_id) %>%
mutate(counts = scale(counts)) %>%
spread(key = age_group, value = counts) %>%
column_to_rownames(var = 'ensembl_id') %>%
subset(select = -transition)
## Joining, by = "gene"
colnames(z_scores) <- c("Group 1", "Group 2", "Group 3", "Group 4", "Group 5")
out <- pheatmap(t(z_scores), cluster_rows = FALSE, show_colnames = FALSE, fontsize = 22)

gene_order <- rownames(z_scores[out$tree_col[["order"]], ])
pheatmap(t(z_scores[gene_order, ]), cluster_rows = FALSE, cluster_cols = FALSE, show_colnames = TRUE,
fontsize = 22, fontsize_col = 12)

Group1-specific genes
DE_genes <- read.delim(paste0(dir, "Data/DE_Group1.csv"), sep = ",") %>%
subset(select = c(ensembl_id))
z_scores <- inner_join(counts, DE_genes) %>%
subset(select = -c(gene)) %>%
group_by(ensembl_id) %>%
mutate(counts = scale(counts)) %>%
spread(key = age_group, value = counts) %>%
column_to_rownames(var = 'ensembl_id')
## Joining, by = "ensembl_id"
colnames(z_scores) <- c("Group 1", "Group 2", "Group 3", "Group 4", "Group 5")
pheatmap(t(z_scores), cluster_rows = FALSE, show_colnames = FALSE, fontsize = 22)

Group4-5-specific genes
DE_genes <- read.delim(paste0(dir, "Data/DE_Group4_5.csv"), sep = ",") %>%
subset(select = c(gene))
z_scores <- inner_join(counts, DE_genes) %>%
subset(select = -c(gene)) %>%
group_by(ensembl_id) %>%
mutate(counts = scale(counts)) %>%
spread(key = age_group, value = counts) %>%
column_to_rownames(var = 'ensembl_id')
## Joining, by = "gene"
colnames(z_scores) <- c("Group 1", "Group 2", "Group 3", "Group 4", "Group 5")
pheatmap(t(z_scores), cluster_rows = FALSE, show_colnames = FALSE, fontsize = 22)

Group5-specific genes
DE_genes <- read.delim(paste0(dir, "Data/DE_Group5.csv"), sep = ",") %>%
subset(select = c(ensembl_id))
z_scores <- inner_join(counts, DE_genes) %>%
subset(select = -c(gene)) %>%
group_by(ensembl_id) %>%
mutate(counts = scale(counts)) %>%
spread(key = age_group, value = counts) %>%
column_to_rownames(var = 'ensembl_id')
## Joining, by = "ensembl_id"
colnames(z_scores) <- c("Group 1", "Group 2", "Group 3", "Group 4", "Group 5")
pheatmap(t(z_scores), cluster_rows = FALSE, show_colnames = FALSE, fontsize = 22)

Upregulated Group5-specific genes
DE_genes <- read.delim(paste0(dir, "Data/DE_Group5_up.csv"), sep = ",") %>%
subset(select = c(ensembl_id))
z_scores <- inner_join(counts, DE_genes) %>%
subset(select = -c(gene)) %>%
group_by(ensembl_id) %>%
mutate(counts = scale(counts)) %>%
spread(key = age_group, value = counts) %>%
column_to_rownames(var = 'ensembl_id')
## Joining, by = "ensembl_id"
colnames(z_scores) <- c("Group 1", "Group 2", "Group 3", "Group 4", "Group 5")
breakslist = seq(-1.5, 1.5, by = 0.1)
pheatmap(t(z_scores), cluster_rows = FALSE, show_colnames = FALSE, fontsize = 30,
breaks = breakslist, color = colorRampPalette(rev(brewer.pal(n = 7, name = "RdYlBu")))(length(breakslist)))

Downregulated Group5-specific genes
DE_genes <- read.delim(paste0(dir, "Data/DE_Group5_down.csv"), sep = ",") %>%
subset(select = c(ensembl_id))
z_scores <- inner_join(counts, DE_genes) %>%
subset(select = -c(gene)) %>%
group_by(ensembl_id) %>%
mutate(counts = scale(counts)) %>%
spread(key = age_group, value = counts) %>%
column_to_rownames(var = 'ensembl_id')
## Joining, by = "ensembl_id"
colnames(z_scores) <- c("Group 1", "Group 2", "Group 3", "Group 4", "Group 5")
breakslist = seq(-1.5, 1.5, by = 0.1)
pheatmap(t(z_scores), cluster_rows = FALSE, show_colnames = FALSE, fontsize = 30,
breaks = breakslist, color = colorRampPalette(rev(brewer.pal(n = 7, name = "RdYlBu")))(length(breakslist)))

Upregulated Group45-specific genes
DE_genes <- read.delim(paste0(dir, "Data/DE_Group45_up.csv"), sep = ",") %>%
subset(select = c(gene))
z_scores <- inner_join(counts, DE_genes) %>%
subset(select = -c(gene)) %>%
group_by(ensembl_id) %>%
mutate(counts = scale(counts)) %>%
spread(key = age_group, value = counts) %>%
column_to_rownames(var = 'ensembl_id')
## Joining, by = "gene"
colnames(z_scores) <- c("Group 1", "Group 2", "Group 3", "Group 4", "Group 5")
pheatmap(t(z_scores), cluster_rows = FALSE, show_colnames = FALSE, fontsize = 22)

Downregulated Group45-specific genes
DE_genes <- read.delim(paste0(dir, "Data/DE_Group45_down.csv"), sep = ",") %>%
subset(select = c(gene))
z_scores <- inner_join(counts, DE_genes) %>%
subset(select = -c(gene)) %>%
group_by(ensembl_id) %>%
mutate(counts = scale(counts)) %>%
spread(key = age_group, value = counts) %>%
column_to_rownames(var = 'ensembl_id')
## Joining, by = "gene"
colnames(z_scores) <- c("Group 1", "Group 2", "Group 3", "Group 4", "Group 5")
pheatmap(t(z_scores), cluster_rows = FALSE, show_colnames = FALSE, fontsize = 22)

Upregulated Group4-specific genes
DE_genes <- read.delim(paste0(dir, "Data/DE_Group4_up.csv"), sep = ",") %>%
subset(select = c(gene))
z_scores <- inner_join(counts, DE_genes) %>%
subset(select = -c(gene)) %>%
group_by(ensembl_id) %>%
mutate(counts = scale(counts)) %>%
spread(key = age_group, value = counts) %>%
column_to_rownames(var = 'ensembl_id')
## Joining, by = "gene"
colnames(z_scores) <- c("Group 1", "Group 2", "Group 3", "Group 4", "Group 5")
pheatmap(t(z_scores), cluster_rows = FALSE, show_colnames = FALSE, fontsize = 22)

Downregulated Group4-specific genes
DE_genes <- read.delim(paste0(dir, "Data/DE_Group4_down.csv"), sep = ",") %>%
subset(select = c(gene))
z_scores <- inner_join(counts, DE_genes) %>%
subset(select = -c(gene)) %>%
group_by(ensembl_id) %>%
mutate(counts = scale(counts)) %>%
spread(key = age_group, value = counts) %>%
column_to_rownames(var = 'ensembl_id')
## Joining, by = "gene"
colnames(z_scores) <- c("Group 1", "Group 2", "Group 3", "Group 4", "Group 5")
pheatmap(t(z_scores), cluster_rows = FALSE, show_colnames = FALSE, fontsize = 22)

Upregulated Group1-specific genes
DE_genes <- read.delim(paste0(dir, "Data/DE_Group1_up.csv"), sep = ",") %>%
subset(select = c(ensembl_id))
z_scores <- inner_join(counts, DE_genes) %>%
subset(select = -c(gene)) %>%
group_by(ensembl_id) %>%
mutate(counts = scale(counts)) %>%
spread(key = age_group, value = counts) %>%
column_to_rownames(var = 'ensembl_id')
## Joining, by = "ensembl_id"
colnames(z_scores) <- c("Group 1", "Group 2", "Group 3", "Group 4", "Group 5")
breakslist = seq(-1.5, 1.5, by = 0.1)
pheatmap(t(z_scores), cluster_rows = FALSE, show_colnames = FALSE, fontsize = 30,
breaks = breakslist, color = colorRampPalette(rev(brewer.pal(n = 7, name = "RdYlBu")))(length(breakslist)))

Downregulated Group1-specific genes
DE_genes <- read.delim(paste0(dir, "Data/DE_Group1_down.csv"), sep = ",") %>%
subset(select = c(ensembl_id))
z_scores <- inner_join(counts, DE_genes) %>%
subset(select = -c(gene)) %>%
group_by(ensembl_id) %>%
mutate(counts = scale(counts)) %>%
spread(key = age_group, value = counts) %>%
column_to_rownames(var = 'ensembl_id')
## Joining, by = "ensembl_id"
colnames(z_scores) <- c("Group 1", "Group 2", "Group 3", "Group 4", "Group 5")
breakslist = seq(-1.5, 1.5, by = 0.1)
pheatmap(t(z_scores), cluster_rows = FALSE, show_colnames = FALSE, fontsize = 30,
breaks = breakslist, color = colorRampPalette(rev(brewer.pal(n = 7, name = "RdYlBu")))(length(breakslist)))
